MDDI 演講稿 · 2024-01-29
楊莉明部長在 Explore AI 活動上的演講
要點
- • 新加坡 AI 治理觀：「治理 ≠ 監管」——治理還包括基礎設施（算力 + 工具 + 治理框架）+ 能力（產業、公司、人）+ 夥伴關係（包容、共學、跨政府）。
- • Trailblazers 100/100 目標（100 個專案 100 天）已輕鬆完成；6 個月內 46 個專案已造出 MVP。
- • 案例：南洋理工學院（NYP）用生成式 AI 幫助講師快速跟上 IT 領域變化、設計課程；Doctor Anywhere 把轉診到 24×7「Doctor Anytime」。
- • Trailblazers 2.0 即將啟動——規模至少是當前的 1.5 倍。當前專案僅時間節省一項——預估每年價值 1000 萬新元以上。
完整譯文（繁體中文）
MDDI 英文原文譯文 · 翻譯日期: 2026-05-03
本文已從早期版本的網站遷移過來——格式可能有不一致之處。
1. 感謝 Google 再次接待我。我看到臺下許多同仁——很高興回來。兩週前我在瑞士達沃斯——見到許多 Google 同仁。政府與 Google 的所有活動都指向一個好目的——我們都關心 AI 能做什麼。不只是為公司或行業——也許聽起來宏大或過分雄心——我們也關心——我們能做什麼幫助這個世界。
2. 在達沃斯——AI 不出意外地高居議程。圍繞 AI 的一個問題——是「我們到底需要什麼才能把它治理好」。與新加坡生態打交道的人會注意到——在治理上——我們不會只把它當作監管。監管當然是良好治理的一部分——但在數字、特別是 AI 上——我們必須確保有支撐活動的良好基礎設施。
3. 因此——當我們提出更新版《國家 AI 戰略》時——我們認為——產業、研究、政府這些「活動驅動力」——只能在「基礎設施」語境的支撐下——才能走得很遠。這種基礎設施包括——算力與工具的可獲得性、各項治理框架的就位。所以——基礎設施（以及與之配套的「公用事業」）——是絕對必要的。
4. 良好治理的另一個非常重要的面向——是構建能力。這裡說的是——產業、公司、人三層面的能力。如果沒有人幫你把它變為現實——幾乎不可能讓 AI 在多個行業中被部署。
5. 夥伴關係——又一個良好治理的重要面向。我們「為包容而合作」。包容意味著——人們不僅能接觸到工具——還被給予機會發展「能用好這些工具」的技能。也意味著——「為彼此學習而合作」。AI Verify 就是一個很好的例子。要把實操級測試工具放就位——我們需要搞清楚——當企業部署 AI 系統並使用這些測試工具時——他們學到了什麼？我們如何改進這些工具的設計與部署？當然——夥伴關係也延伸到與其他政府的合作。這就是我們本週晚些時候要嘗試的事——與 ASEAN 大家庭的同行、並在全球層面。
6. 我今天分享所有這些——是因為今天「Trailblazers」的重大里程碑——確實勾選了我所描述的所有方框——良好治理的力量、把基礎設施/公用事業/工具彙集起來、構建企業與人的能力、嘗試理解如何在落地 AI 時既包容又負責任、以及「彼此學習」的理念。所以——我真的想感謝 Google——讓這件事發生——並如此熱情地與我們合作。
7. 與所有政府努力一樣——我們總會問自己——這些專案裡最大的回報是什麼？我也對 Trailblazers 這樣問過。一開始——我們希望看到「100 天 100 個專案」——這件事很容易達成——拿到 100 個專案沒問題。下一個問題——這些專案能不能成為「最小可行產品」（MVP）？答案是——能。事實上——僅 6 個月裡——其中 46 個就已經做出了 MVP。
8. 我走訪的幾支團隊中——遇到一支非常有趣的——南洋理工學院（NYP）。我曾在 NYP 董事會任職——所以這種「生成式 AI 可能幫助講師設計回應產業需求的課程，以學生為受益者」的想法讓我很感興趣。在 IHL 工作過的人都知道——設計一門課程、整合一份課綱——通常要花幾個月。但在 IT 領域——6 個月裡很多事就變了。因此——這種新工具有可能讓講師——快速感知所授領域裡發生的事——並把課程設計與所需材料整合起來——以達成學習成果。
9. 另一個引起我注意的專案——是 Doctor Anywhere。作為一名病人——你可能需要看專科醫生——但首先要找到合適的專科醫生——這通常依賴於「代理人」——他會基於你的病史與保險計劃給建議。因此——Doctor Anywhere 在 Trailblazers 專案裡開始嘗試——能否克服「病人在專科轉診上的困難」。藉助生成式 AI 工具——Doctor Anywhere 現在能成為「Doctor Anytime」——24×7 在病人需要時提供。
10. 藉助生成式 AI——NYP 能從「節省時間 + 提升課程時效」中受益；Doctor Anywhere 能改善客戶體驗——並對感到焦慮的病人有所幫助。這些事——我們如何量化收益？如何衡量它們的價值與影響？說實話並不容易——病人滿意度的改善、畢業一屆屆學生帶著更相關技能進入職場所帶來的好處——並不易測量。但我們仍必須嘗試。我們僅基於 Trailblazers 中畢業的產業專案——做了一個保守評估——發現僅在「時間節省與效率提升」上——估值每年超過 1000 萬新元。
11. 現在——我很高興地說——在新加坡經濟發展局（EDB）同仁加快評估的支援下——我們能推進「Trailblazers 2.0」——它至少是當前專案的 1.5 倍規模。基於此——我們能保守地說——潛在的時間節省一定會超過當前的執行。但「美元價值」之外——更重要的是——我們正在新加坡內部——快速構建起這種「想象力與興趣」——去用生成式 AI 工具——顯著改進與改造企業的工作方式——並通過「讓員工做得更好」來提升客戶滿意度。我把這一切——視為對我們「在這裡成長 AI 生態」非常有益。
12. 在此——再次感謝邀請。我祝賀所有 Trailblazers 畢業生——以及「Transformation Award」與「Innovation Award」的獲獎者。
13. 謝謝。
演講 PDF 版本
英文原文
MDDI 官網原始記錄 · 抓取日期: 2026-05-02
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1. Thank you Google for hosting me again. I see many colleagues in the audience, and I am happy to be back. Two weeks ago, I was in Davos, Switzerland where I met many colleagues from Google. The activities that the Government has with Google have are all towards a good cause - we are all interested in seeing what AI can do. Not just for companies or industries - but it may sound lofty and overly ambitious - we are interested to see what we can do to help the world.
2. In Davos, unsurprisingly, AI was very high on the agenda. One of the questions around AI is about what we really need to govern it well. For those who have interacted with the Singaporean ecosystem, they notice that in terms of governance, we tend not to just think of it as just regulations. Regulations are certainly part of good governance, but in digital, and certainly in AI, we have to make sure there is good infrastructure to support the activities.
3. So, when we put forward our refreshed National AI Strategy, we felt that the activity drivers of industry, research, and government can only push far ahead if supported within the context of that infrastructure. Such infrastructure would include having the compute and tools available, and the various governance frameworks in place. So, the infrastructure and utilities, which go along with that infrastructure, are absolutely essential.
4. Another very important aspect of good governance is in building capabilities. By this, we are talking about capabilities within industries, companies, and people. It is next to impossible to have AI deployed across many different sectors if you do not have the people to help make that a reality.
5. Partnerships is yet another important aspect of good governance. We partner for inclusion. Inclusion means making sure that people not only have access to the tools, but they are provided with opportunities to grow the skills that will enable them to use these tools well. It also means partnering to learn together. AI Verify is a very good example. If we want to be able to put in place practical testing tools, we need to figure out - when companies deploy the AI systems and use these testing tools, what are they learning and how can we improve the way in which these tools are designed and deployed? Of course, partnership also extends to partnering with other governments. And that is what we are attempting to do later this week with our colleagues in the ASEAN family, but also at the global level.
6. The reason I am sharing all this today, is that today's major milestone for Trailblazers actually ticks all of the boxes that I described - the power of good governance; bringing together the infrastructure, utilities, and tools; building enterprise and people capabilities; trying to understand how you can be inclusive and yet, at the same time, responsible in the way we implement AI; the idea of us all learning together. So, I really want to thank Google for making this happen and for partnering with us so enthusiastically.
7. As with all government efforts, we always ask ourselves - what has been the biggest payoff in these projects? And I attempted to do the same for Trailblazers. When we started, we wanted to be able to see 100 projects within 100 days. That was achieved easily as we had no problem getting 100 projects. The next question you ask – are the projects able to become Minimum Viable Products (MVP)? And the answer is, yes. In fact, in the short period of just about six months, 46 of them have in fact built an MVPs.
8. Among the several teams that I visited, I came across this very interesting one by Nanyang Polytechnic (NYP). I used to serve on the Board of NYP, so I was quite intrigued by the idea that generative AI potentially can help instructors design curriculum courses that respond to the industry needs for their students’ benefit. For those of us who have been involved with institutes of higher learning, we know that designing a course and pulling together a curriculum usually takes months; but in the field of IT, many changes can take place in six months. Hence, this new tool can potentially enable the instructors to quickly get a sense of what is happening in the field that they are required to instruct in, and then to put together a course design together with the course materials that are needed to achieve the learning outcomes.
9. The other project that caught my attention was by Doctor Anywhere. As a patient, you may need to see a specialist, but first you have to identify the right specialist; for that to happen, it would usually often depend on an agent who would advise you depending on your own medical history and insurance programme. Hence, Doctor Anywhere started working on the Trailblazers project to see whether they could overcome difficulties that patients have in accessing specialist referral services. With the use of a generative AI tool, Doctor Anywhere can now be Doctor Anytime, that is to be offered anytime, 24/7, when the patient needs it.
10. With Generative AI, NYP can potentially benefit from time savings and enhanced currency in their curriculum to the students. With Doctor Anywhere, they experienced enhancements to customer experience and being helpful to patients who feel a sense of anxiety. For these things, how do we quantify the benefits? How do we measure their value and their impact? The truth is, it is not so easy. It is not so easy to measure the value of improved patient satisfaction, and it is not so easy to quantify how much more beneficial it is for every graduating cohort of students to come out into the workforce with more relevant skills than they did before. But still, we must try. We did a modest assessment based on just the graduating industry projects from Trailblazers, and found that in terms of time savings and greater efficiency, the estimate is in excess of $10 million savings annually.
11. Now, I am very happy to say that with the help and support of our colleagues in the EDB that have fast tracked their assessment, we can move ahead with Trailblazer 2.0, which is at least 1.5 times bigger than the current programme. With that, we could very modestly say that the potential time savings will definitely exceed the current run. But beyond the dollar value is the idea that we are building up very quickly this capacity within Singapore, and the imagination and interest to use the tools of Generative AI to significantly improve and transform the way business is done and enhance customer satisfaction by helping employees do a better job. So, I see all of this as really being very beneficial for how we are trying to grow the AI ecosystem here.
12. On that note, thank you once again for inviting me. I want to congratulate all of the Trailblazers graduates, and the ‘Transformation Award’ winners and ‘Innovation Award’ winners.
13. Thank you.
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